Tomasz Puton: "This will probably be a very interesting talk. Just can't wait."

arne: "Not just interesting, but most likely great. Svante is a fantastic speaker"

Barb Bryant: "If you’re interested in human history, the genome is a great source of information. To reconstruct history, we compare sequences of people (and other species) living today. We use models of how DNA changes over time to understand the differences that exist today.
This is an indirect way to study history, because we are reconstructing from the present what we think has happened in the past."

arne: "Human FoxP2 in mouse: The mouse can not speak ! Large scale phenotype study (323 phenotypic traits). -> More cautious in a novel area (stays close to the wall). No difference after 3 minutes. Second phenotype: Altered vocalization !!!"

arne: "When grouping mutations into pathways up to 85% of GBM have a muation in the most important pathways, while individual genes are down to a few %"

Barb Bryant: "Each oncogene may have relatively low frequency across patients; but when you group genes across pathways, a pathway may explain a large fraction of patients with a given type of cancer."

Barb Bryant: "Metastatic tumor samples have more copy number changes than primary tumors. Not surprising. But maybe primary samples with more copy number changes than others are more likely to metastasize? Generally, better outcome with fewer somatic copy number changes."

Barb Bryant: "So you have a probability distribution for each Wij, which represents the interaction between element i and element j. I'm not really getting how you "update" these probability distributions in the iterative steps. I do understand that at the end you take the most "certain" (narrowest) distribution and fix its value (some Wij) at the most probable value, then update all the other Wij's given this fixation. And so on. To get your final model in a sort of greedy fashion."

Barb Bryant: "And by the way, the underlying model is a simple differential equation sort of thing: change of one variable xi is a sigmoidal function of weighted (Wij) sum of all variables xj, less a decay term."

Barb Bryant: "Chris: yes - if the network model allows you to predict correctly the result of a particular perturbation applied to a particular node, then you can simulate using that model."

Barb Bryant: "Question: with a big network, how many experiments will you need to model?"

Barb Bryant: "Chris: Good question. Could use an entropy measure. Help us figure this out. Help us design the experiments. It's important because of the costs of experiment. This is going to be broadly applicable in cell biology."

Shannon McWeeney: "bb - he said one should see if approach is useful by confronting with real data"

Barb Bryant: "Chris gets at the difference between a model that tells a story and a model that is truly predictive."

Barb Bryant: "Question: yes, but, what are the semantics of the graph? What kinds of interaction? Answer: The semantics are in the mathematics of your model."

Barb Bryant: "Question: mean field approach is interesting. Compared to Monte Carlo approach, you are assuming some decoupling. Loss of posterior coupling between weights - is that an issue?"

Barb Bryant: "Chris: If you look at a coupled system overall, the extent to which the algorithms work depends on correlations within the system. Long-range (in terms of network distance) correlations are problematic. There are some clever approaches to handle some of this. Mentions non-ergotic space; deal with parts of space separately or iteratively."

Barb Bryant: "Francis Galton was a cousin of Darwin. Darwin didn’t explain the source of variation. Galton focused on this; he measured the heights of parents and their offspring, and found a relationship. He invented regression analysis to draw the line. The slope of the line is related to the inheritability of the disease."

Dawei lin: "It was studied by the cousin of Darwin, Francis Galton (1885)"

Barb Bryant: "Muller 1920 paper: 4 chromosomes in fly – 3 contain genes that influence the trait truncate wing. Muller wrote about implications for human traits, like psychological traits. Said that traits were going to be too complicated. Said you could figure out by looking at population, but not looking at Mendelian inheritance in families."

Dawei lin: "Muller 1920 suggested that it needed to do study on a population."

Barb Bryant: "In 2005 we abandoned a monopolistic capillary electrophoresis; instead we have a couple and now 21 different technologies for sequencing. Resulted in a jump in rate of change of sequencing capacity"

arne: "He thinks that many of the sequencing companies will find a niche :)"

arne: "Sidetrack: One friend said when he started his PhD it took 6 month to sequence a bacteria and 6-60 month to analyse it. Not it takes 6 minuted to sequence it and still 6-60 month to analyze it."

Barb Bryant: "Example of freeing up a codon by changing those codons to a different one./"

arne: "Is this not just the analysis. Not the sequence ? (or did I miss a link)"

Christiaan Klijn: "See the 'Datasets' header -> you can get 500k Affy data as well as exome"

Barb Bryant: "Metabolic engineering example. Historically, you'd get obsessed with one step in the pathway and overproduce one enzyme. But then you'd get product inhibition, or the product might be toxic."

arne: "Would be nice with a map to the reference genome as well, but guess that can be done"

Barb Bryant: "Tan Ince cultured two kinds of normal human mammary epithelial cells. He transformed them with oncogenes, resulting in different types of tumors."

Barb Bryant: "Concludes that the nature of the normal cell of origin is a strong determinant of the phenotype of the primary tumor, and whether it metastasizes. The playing field is tilted in the beginning."

Barb Bryant: "Self-renewing stem cells produce either more stem cells or transit amplifying cells which in turn lead to post-mitotic differentiated cells. Only the self-renewing stem cell could seed a new tumor."

Barb Bryant: "It seems likely that most of the invasion-metastasis program can happen without need for additional mutations; rather use signaling from microenvironment."

Barb Bryant: "P. Gupta transformed human primary melanocytes (pigmentation in the skin) with a cocktail of oncogenes. Found that in contrast to transformed epithelial cells, there was much higher likelihood of metastasis. Again, cell of origin is important in future behavior."

Barb Bryant: "One TF, Slug, was found to enable melanoma metastasis. (Even though the primary tumors grew a little faster.)"

Barb Bryant: "Another TF, FOXC2, when expressed in epithelial cells induces migration and invasion. A subset of breast cancers have high levels of nuclear FOXC2, and these are more aggressive breast cancers."

Barb Bryant: "Speculates that different networks of EMT-inducing factors might program metastasis in different cell types./"

Barb Bryant: "Stem cells identified by high CD44 and low CD24. (CD's are markers on cell surface which can be assayed fairly easily.)"

Barb Bryant: "There are various ways to make cells acquire stem cell characteristics."

Barb Bryant: "Most current chemotherapies preferentially kill non-cancer-stem-cells. The remaining stem cells can repopulate the tumor and are often more resistant to therapies."

Barb Bryant: "Gupta & Onder tested CSCs and non_CSCs with a bunch of drugs. There are some CSC-targeted agents (Salinomycin, Abamectin). Of 16,000 compounds only about a dozen preferentially killed CSCs as opposed to non_CSCs. Many were the other way round."

Barb Bryant: "This probably won't be the "answer". Christine Chaffer noticed that there were some floating cells in 2D cultured human mammary epithelial cells. She grew these up; these look more like CSCs."

Barb Bryant: "Interestingly, she found that non-CSCs could generate CSCs."

Barb Bryant: "Hm, isn't this kind of pouring cold water on the excitement about CSCs as drug targets? Or maybe you have to target both CSCs and non-CSCs simultaneously."

Barb Bryant: "Q: cancer biologists like to study druggable genome. But transcription factors seem most important. A: expression of TFs is controlled by cytoplasmic factors. Might want to go after those. Drugging the TF itself might be hard, but the signaling pathways might be more druggable."

Barb Bryant: "Q: has it been shown that change in the two forms of cadherins match the change in CD expression, and are these correlated with morphology? A: I showed that: CD44 high cells shut down E-cadherin; they expression vimentin, and other mesenchymal markers. I don't know whether CD44 is useful for non-mammary epithelial tissues."

Barb Bryant: "Q: So do normal non-SCs generate SCs? A: Yes. Same differences as in cancer."